{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "wZ58h5LMwBhx"
   },
   "source": [
    "# **If you are using Colab for free, we highly recommend you active the T4 GPU hardware accelerator. Our models are designed to run with at least 16GB of RAM, activating T4 will grant the notebook 16GB of GDDR6 RAM as opposed to the 13GB Colab gives automatically.**\n",
    "# **To active T4:**\n",
    "# **1.   click on the \"Runtime\" tab**\n",
    "# **2.   click on \"Change runtime type\"**\n",
    "# **3.   select T4 GPU under Hardware Accelerator**\n",
    "# **NOTE: there is a weekly usage limit on using T4 for free**\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "WIyD5iacAKHg",
    "outputId": "7fd9b314-8b68-4e3d-e29f-3edad144d316"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting llmware\n",
      "  Downloading llmware-0.3.0-py3-none-any.whl (56.0 MB)\n",
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      "\u001b[?25hCollecting boto3>=1.24.53 (from llmware)\n",
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      "Installing collected packages: psycopg-binary, psycopg, pgvector, jmespath, dnspython, colorama, pymongo, botocore, s3transfer, boto3, llmware\n",
      "Successfully installed boto3-1.34.120 botocore-1.34.120 colorama-0.4.6 dnspython-2.6.1 jmespath-1.0.1 llmware-0.3.0 pgvector-0.2.4 psycopg-3.1.17 psycopg-binary-3.1.17 pymongo-4.7.3 s3transfer-0.10.1\n",
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      "Collecting nvidia-cuda-nvrtc-cu12==12.1.105 (from torch)\n",
      "  Using cached nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB)\n",
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      "Collecting nvidia-cudnn-cu12==8.9.2.26 (from torch)\n",
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      "Collecting nvidia-cublas-cu12==12.1.3.1 (from torch)\n",
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      "Collecting nvidia-cufft-cu12==11.0.2.54 (from torch)\n",
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      "Installing collected packages: nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12\n",
      "Successfully installed nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.20.5 nvidia-nvjitlink-cu12-12.5.40 nvidia-nvtx-cu12-12.1.105\n",
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     ]
    }
   ],
   "source": [
    "!pip install llmware\n",
    "!pip install torch\n",
    "!pip install transformers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "OjhR95nTB5Ye"
   },
   "outputs": [],
   "source": [
    "import time\n",
    "from llmware.prompts import Prompt\n",
    "from llmware.models import ModelCatalog"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "Vu5OlNLsB_rL"
   },
   "outputs": [],
   "source": [
    "llm_models = ModelCatalog().list_generative_models()\n",
    "llm_local_models = ModelCatalog().list_generative_local_models()\n",
    "llm_open_source_models = ModelCatalog().list_open_source_models()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "GX--TIaACSvr",
    "outputId": "a9fa3e82-93fd-4852-a182-3ea6d3f9a852"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "models:  0 Meta-Llama-3-8B HFGenerativeModel\n",
      "models:  1 Meta-Llama-3-8B-Instruct HFGenerativeModel\n",
      "models:  2 QuantFactory/Meta-Llama-3-8B-GGUF GGUFGenerativeModel\n",
      "models:  3 QuantFactory/Meta-Llama-3-8B-Instruct-GGUF GGUFGenerativeModel\n",
      "models:  4 TheBloke/Llama-2-7B-Chat-GGUF GGUFGenerativeModel\n",
      "models:  5 TheBloke/OpenHermes-2.5-Mistral-7B-GGUF GGUFGenerativeModel\n",
      "models:  6 TheBloke/Starling-LM-7B-alpha-GGUF GGUFGenerativeModel\n",
      "models:  7 TheBloke/zephyr-7B-beta-GGUF GGUFGenerativeModel\n",
      "models:  8 bartowski/Meta-Llama-3-8B-Instruct-GGUF GGUFGenerativeModel\n",
      "models:  9 bling-answer-tool GGUFGenerativeModel\n",
      "models:  10 bling-phi-3-gguf GGUFGenerativeModel\n",
      "models:  11 bling-stablelm-3b-tool GGUFGenerativeModel\n",
      "models:  12 dragon-llama-answer-tool GGUFGenerativeModel\n",
      "models:  13 dragon-mistral-answer-tool GGUFGenerativeModel\n",
      "models:  14 dragon-yi-answer-tool GGUFGenerativeModel\n",
      "models:  15 llmware/bling-1.4b-0.1 HFGenerativeModel\n",
      "models:  16 llmware/bling-1b-0.1 HFGenerativeModel\n",
      "models:  17 llmware/bling-cerebras-1.3b-0.1 HFGenerativeModel\n",
      "models:  18 llmware/bling-falcon-1b-0.1 HFGenerativeModel\n",
      "models:  19 llmware/bling-phi-3 HFGenerativeModel\n",
      "models:  20 llmware/bling-red-pajamas-3b-0.1 HFGenerativeModel\n",
      "models:  21 llmware/bling-sheared-llama-1.3b-0.1 HFGenerativeModel\n",
      "models:  22 llmware/bling-sheared-llama-2.7b-0.1 HFGenerativeModel\n",
      "models:  23 llmware/bling-stable-lm-3b-4e1t-v0 HFGenerativeModel\n",
      "models:  24 llmware/bling-tiny-llama-v0 HFGenerativeModel\n",
      "models:  25 llmware/dragon-deci-6b-v0 HFGenerativeModel\n",
      "models:  26 llmware/dragon-deci-7b-v0 HFGenerativeModel\n",
      "models:  27 llmware/dragon-falcon-7b-v0 HFGenerativeModel\n",
      "models:  28 llmware/dragon-llama-7b-gguf GGUFGenerativeModel\n",
      "models:  29 llmware/dragon-llama-7b-v0 HFGenerativeModel\n",
      "models:  30 llmware/dragon-mistral-7b-gguf GGUFGenerativeModel\n",
      "models:  31 llmware/dragon-mistral-7b-v0 HFGenerativeModel\n",
      "models:  32 llmware/dragon-red-pajama-7b-v0 HFGenerativeModel\n",
      "models:  33 llmware/dragon-stablelm-7b-v0 HFGenerativeModel\n",
      "models:  34 llmware/dragon-yi-6b-gguf GGUFGenerativeModel\n",
      "models:  35 llmware/dragon-yi-6b-v0 HFGenerativeModel\n",
      "models:  36 llmware/slim-category HFGenerativeModel\n",
      "models:  37 llmware/slim-emotions HFGenerativeModel\n",
      "models:  38 llmware/slim-intent HFGenerativeModel\n",
      "models:  39 llmware/slim-ner HFGenerativeModel\n",
      "models:  40 llmware/slim-nli HFGenerativeModel\n",
      "models:  41 llmware/slim-q-gen-phi-3 HFGenerativeModel\n",
      "models:  42 llmware/slim-q-gen-tiny HFGenerativeModel\n",
      "models:  43 llmware/slim-qa-gen-phi-3 HFGenerativeModel\n",
      "models:  44 llmware/slim-qa-gen-tiny HFGenerativeModel\n",
      "models:  45 llmware/slim-ratings HFGenerativeModel\n",
      "models:  46 llmware/slim-sentiment HFGenerativeModel\n",
      "models:  47 llmware/slim-sql-1b-v0 HFGenerativeModel\n",
      "models:  48 llmware/slim-tags HFGenerativeModel\n",
      "models:  49 llmware/slim-topics HFGenerativeModel\n",
      "models:  50 microsoft/Phi-3-mini-128k-instruct HFGenerativeModel\n",
      "models:  51 microsoft/Phi-3-mini-4k-instruct HFGenerativeModel\n",
      "models:  52 microsoft/Phi-3-mini-4k-instruct-gguf GGUFGenerativeModel\n",
      "models:  53 slim-boolean HFGenerativeModel\n",
      "models:  54 slim-boolean-tool GGUFGenerativeModel\n",
      "models:  55 slim-category-tool GGUFGenerativeModel\n",
      "models:  56 slim-emotions-tool GGUFGenerativeModel\n",
      "models:  57 slim-extract HFGenerativeModel\n",
      "models:  58 slim-extract-tool GGUFGenerativeModel\n",
      "models:  59 slim-intent-tool GGUFGenerativeModel\n",
      "models:  60 slim-ner-tool GGUFGenerativeModel\n",
      "models:  61 slim-nli-tool GGUFGenerativeModel\n",
      "models:  62 slim-q-gen-phi-3-tool GGUFGenerativeModel\n",
      "models:  63 slim-q-gen-tiny-tool GGUFGenerativeModel\n",
      "models:  64 slim-qa-gen-phi-3-tool GGUFGenerativeModel\n",
      "models:  65 slim-qa-gen-tiny-tool GGUFGenerativeModel\n",
      "models:  66 slim-ratings-tool GGUFGenerativeModel\n",
      "models:  67 slim-sa-ner HFGenerativeModel\n",
      "models:  68 slim-sa-ner-tool GGUFGenerativeModel\n",
      "models:  69 slim-sentiment-tool GGUFGenerativeModel\n",
      "models:  70 slim-sql-tool GGUFGenerativeModel\n",
      "models:  71 slim-summary HFGenerativeModel\n",
      "models:  72 slim-summary-tool GGUFGenerativeModel\n",
      "models:  73 slim-tags-3b HFGenerativeModel\n",
      "models:  74 slim-tags-3b-tool GGUFGenerativeModel\n",
      "models:  75 slim-tags-tool GGUFGenerativeModel\n",
      "models:  76 slim-topics-tool GGUFGenerativeModel\n",
      "models:  77 slim-xsum HFGenerativeModel\n",
      "models:  78 slim-xsum-tool GGUFGenerativeModel\n",
      "models:  79 tiny-llama-chat-gguf GGUFGenerativeModel\n",
      "models:  80 whisper-cpp-base WhisperCPPModel\n",
      "models:  81 whisper-cpp-base-english WhisperCPPModel\n",
      "models:  82 whisper-cpp-tiny-diarize WhisperCPPModel\n"
     ]
    }
   ],
   "source": [
    "for i, models in enumerate(llm_local_models):\n",
    "  print(\"models: \", i, models[\"model_name\"], models[\"model_family\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "l0Rv8Cd6CoqT"
   },
   "outputs": [],
   "source": [
    "pytorch_generative_models = [\"llmware/bling-1b-0.1\", \"llmware/bling-tiny-llama-v0\", \"llmware/bling-falcon-1b-0.1\"]\n",
    "gguf_generative_models = [\"bling-answer-tool\", \"bling-phi-3-gguf\",\"llmware/dragon-yi-6b-gguf\"]\n",
    "model_name = gguf_generative_models[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "_VrUvFMrC4Lq"
   },
   "outputs": [],
   "source": [
    "t0 = time.time()\n",
    "test_list = [\n",
    "\n",
    "{\"query\": \"What is the total amount of the invoice?\",\n",
    " \"answer\": \"$22,500.00\",\n",
    " \"context\": \"Services Vendor Inc. \\n100 Elm Street Pleasantville, NY \\nTO Alpha Inc. 5900 1st Street \"\n",
    "            \"Los Angeles, CA \\nDescription Front End Engineering Service $5000.00 \\n Back End Engineering\"\n",
    "            \" Service $7500.00 \\n Quality Assurance Manager $10,000.00 \\n Total Amount $22,500.00 \\n\"\n",
    "            \"Make all checks payable to Services Vendor Inc. Payment is due within 30 days.\"\n",
    "            \"If you have any questions concerning this invoice, contact Bia Hermes. \"\n",
    "            \"THANK YOU FOR YOUR BUSINESS!  INVOICE INVOICE # 0001 DATE 01/01/2022 FOR Alpha Project P.O. # 1000\"},\n",
    "\n",
    "{\"query\": \"What was the amount of the trade surplus?\",\n",
    " \"answer\": \"62.4 billion yen ($416.6 million)\",\n",
    " \"context\": \"Japan’s September trade balance swings into surplus, surprising expectations\"\n",
    "            \"Japan recorded a trade surplus of 62.4 billion yen ($416.6 million) for September, \"\n",
    "            \"beating expectations from economists polled by Reuters for a trade deficit of 42.5 \"\n",
    "            \"billion yen. Data from Japan’s customs agency revealed that exports in September \"\n",
    "            \"increased 4.3% year on year, while imports slid 16.3% compared to the same period \"\n",
    "            \"last year. According to FactSet, exports to Asia fell for the ninth straight month, \"\n",
    "            \"which reflected ongoing China weakness. Exports were supported by shipments to \"\n",
    "            \"Western markets, FactSet added. — Lim Hui Jie\"},\n",
    "\n",
    "{\"query\": \"What was Microsoft's revenue in the 3rd quarter?\",\n",
    " \"answer\": \"$52.9 billion\",\n",
    " \"context\": \"Microsoft Cloud Strength Drives Third Quarter Results \\nREDMOND, Wash. — April 25, 2023 — \"\n",
    "            \"Microsoft Corp. today announced the following results for the quarter ended March 31, 2023,\"\n",
    "            \" as compared to the corresponding period of last fiscal year:\\n· Revenue was $52.9 billion\"\n",
    "            \" and increased 7% (up 10% in constant currency)\\n· Operating income was $22.4 billion \"\n",
    "            \"and increased 10% (up 15% in constant currency)\\n· Net income was $18.3 billion and \"\n",
    "            \"increased 9% (up 14% in constant currency)\\n· Diluted earnings per share was $2.45 \"\n",
    "            \"and increased 10% (up 14% in constant currency).\\n\"},\n",
    "\n",
    "{\"query\": \"When did the LISP machine market collapse?\",\n",
    " \"answer\": \"1987.\",\n",
    " \"context\": \"The attendees became the leaders of AI research in the 1960s.\"\n",
    "            \"  They and their students produced programs that the press described as 'astonishing': \"\n",
    "            \"computers were learning checkers strategies, solving word problems in algebra, \"\n",
    "            \"proving logical theorems and speaking English.  By the middle of the 1960s, research in \"\n",
    "            \"the U.S. was heavily funded by the Department of Defense and laboratories had been \"\n",
    "            \"established around the world. Herbert Simon predicted, 'machines will be capable, \"\n",
    "            \"within twenty years, of doing any work a man can do'.  Marvin Minsky agreed, writing, \"\n",
    "            \"'within a generation ... the problem of creating 'artificial intelligence' will \"\n",
    "            \"substantially be solved'. They had, however, underestimated the difficulty of the problem.  \"\n",
    "            \"Both the U.S. and British governments cut off exploratory research in response \"\n",
    "            \"to the criticism of Sir James Lighthill and ongoing pressure from the US Congress \"\n",
    "            \"to fund more productive projects. Minsky's and Papert's book Perceptrons was understood \"\n",
    "            \"as proving that artificial neural networks approach would never be useful for solving \"\n",
    "            \"real-world tasks, thus discrediting the approach altogether.  The 'AI winter', a period \"\n",
    "            \"when obtaining funding for AI projects was difficult, followed.  In the early 1980s, \"\n",
    "            \"AI research was revived by the commercial success of expert systems, a form of AI \"\n",
    "            \"program that simulated the knowledge and analytical skills of human experts. By 1985, \"\n",
    "            \"the market for AI had reached over a billion dollars. At the same time, Japan's fifth \"\n",
    "            \"generation computer project inspired the U.S. and British governments to restore funding \"\n",
    "            \"for academic research. However, beginning with the collapse of the Lisp Machine market \"\n",
    "            \"in 1987, AI once again fell into disrepute, and a second, longer-lasting winter began.\"},\n",
    "\n",
    "{\"query\": \"When will employment start?\",\n",
    " \"answer\": \"April 16, 2012.\",\n",
    " \"context\": \"THIS EXECUTIVE EMPLOYMENT AGREEMENT (this “Agreement”) is entered \"\n",
    "            \"into this 2nd day of April, 2012, by and between Aphrodite Apollo \"\n",
    "            \"(“Executive”) and TestCo Software, Inc. (the “Company” or “Employer”), \"\n",
    "            \"and shall become effective upon Executive’s commencement of employment \"\n",
    "            \"(the “Effective Date”) which is expected to commence on April 16, 2012. \"\n",
    "            \"The Company and Executive agree that unless Executive has commenced \"\n",
    "            \"employment with the Company as of April 16, 2012 (or such later date as \"\n",
    "            \"agreed by each of the Company and Executive) this Agreement shall be \"\n",
    "            \"null and void and of no further effect.\"},\n",
    "\n",
    "{\"query\": \"What is the current rate on 10-year treasuries?\",\n",
    " \"answer\": \"4.58%\",\n",
    " \"context\": \"Stocks rallied Friday even after the release of stronger-than-expected U.S. jobs data \"\n",
    "            \"and a major increase in Treasury yields.  The Dow Jones Industrial Average gained 195.12 points, \"\n",
    "            \"or 0.76%, to close at 31,419.58. The S&P 500 added 1.59% at 4,008.50. The tech-heavy \"\n",
    "            \"Nasdaq Composite rose 1.35%, closing at 12,299.68. The U.S. economy added 438,000 jobs in \"\n",
    "            \"August, the Labor Department said. Economists polled by Dow Jones expected 273,000 \"\n",
    "            \"jobs. However, wages rose less than expected last month.  Stocks posted a stunning \"\n",
    "            \"turnaround on Friday, after initially falling on the stronger-than-expected jobs report. \"\n",
    "            \"At its session low, the Dow had fallen as much as 198 points; it surged by more than \"\n",
    "            \"500 points at the height of the rally. The Nasdaq and the S&P 500 slid by 0.8% during \"\n",
    "            \"their lowest points in the day.  Traders were unclear of the reason for the intraday \"\n",
    "            \"reversal. Some noted it could be the softer wage number in the jobs report that made \"\n",
    "            \"investors rethink their earlier bearish stance. Others noted the pullback in yields from \"\n",
    "            \"the day’s highs. Part of the rally may just be to do a market that had gotten extremely \"\n",
    "            \"oversold with the S&P 500 at one point this week down more than 9% from its high earlier \"\n",
    "            \"this year.  Yields initially surged after the report, with the 10-year Treasury rate trading \"\n",
    "            \"near its highest level in 14 years. The benchmark rate later eased from those levels, but \"\n",
    "            \"was still up around 6 basis points at 4.58%.  'We’re seeing a little bit of a give back \"\n",
    "            \"in yields from where we were around 4.8%. [With] them pulling back a bit, I think that’s \"\n",
    "            \"helping the stock market,' said Margaret Jones, chief investment officer at Vibrant Industries \"\n",
    "            \"Capital Advisors. 'We’ve had a lot of weakness in the market in recent weeks, and potentially \"\n",
    "            \"some oversold conditions.'\"},\n",
    "\n",
    "{\"query\": \"What is the governing law?\",\n",
    " \"answer\": \"State of Massachusetts\",\n",
    " \"context\": \"19.\tGoverning Law and Procedures. This Agreement shall be governed by and interpreted \"\n",
    "            \"under the laws of the State of Massachusetts, except with respect to Section 18(a) of this Agreement,\"\n",
    "            \" which shall be governed by the laws of the State of Delaware, without giving effect to any \"\n",
    "            \"conflict of laws provisions. Employer and Executive each irrevocably and unconditionally \"\n",
    "            \"(a) agrees that any action commenced by Employer for preliminary and permanent injunctive relief \"\n",
    "            \"or other equitable relief related to this Agreement or any action commenced by Executive pursuant \"\n",
    "            \"to any provision hereof, may be brought in the United States District Court for the federal \"\n",
    "            \"district in which Executive’s principal place of employment is located, or if such court does \"\n",
    "            \"not have jurisdiction or will not accept jurisdiction, in any court of general jurisdiction \"\n",
    "            \"in the state and county in which Executive’s principal place of employment is located, \"\n",
    "            \"(b) consents to the non-exclusive jurisdiction of any such court in any such suit, action o\"\n",
    "            \"r proceeding, and (c) waives any objection which Employer or Executive may have to the \"\n",
    "            \"laying of venue of any such suit, action or proceeding in any such court. Employer and \"\n",
    "            \"Executive each also irrevocably and unconditionally consents to the service of any process, \"\n",
    "            \"pleadings, notices or other papers in a manner permitted by the notice provisions of Section 8.\"},\n",
    "\n",
    "{\"query\": \"What is the amount of the base salary?\",\n",
    " \"answer\": \"$200,000.\",\n",
    " \"context\": \"2.2. Base Salary. For all the services rendered by Executive hereunder, during the \"\n",
    "            \"Employment Period, Employer shall pay Executive a base salary at the annual rate of \"\n",
    "            \"$200,000, payable semimonthly in accordance with Employer’s normal payroll practices. \"\n",
    "            \"Executive’s base salary shall be reviewed annually by the Board (or the compensation committee \"\n",
    "            \"of the Board), pursuant to Employer’s normal compensation and performance review policies \"\n",
    "            \"for senior level executives, and may be increased but not decreased. The amount of any \"\n",
    "            \"increase for each year shall be determined accordingly. For purposes of this Agreement, \"\n",
    "            \"the term “Base Salary” shall mean the amount of Executive’s base salary established \"\n",
    "            \"from time to time pursuant to this Section 2.2. \"},\n",
    "\n",
    "{\"query\": \"Is the expected gross margin greater than 70%?\",\n",
    " \"answer\": \"Yes, between 71.5% and 72.%\",\n",
    " \"context\": \"Outlook NVIDIA’s outlook for the third quarter of fiscal 2024 is as follows:\"\n",
    "            \"Revenue is expected to be $16.00 billion, plus or minus 2%. GAAP and non-GAAP \"\n",
    "            \"gross margins are expected to be 71.5% and 72.5%, respectively, plus or minus \"\n",
    "            \"50 basis points.  GAAP and non-GAAP operating expenses are expected to be \"\n",
    "            \"approximately $2.95 billion and $2.00 billion, respectively.  GAAP and non-GAAP \"\n",
    "            \"other income and expense are expected to be an income of approximately $100 \"\n",
    "            \"million, excluding gains and losses from non-affiliated investments. GAAP and \"\n",
    "            \"non-GAAP tax rates are expected to be 14.5%, plus or minus 1%, excluding any discrete items.\"\n",
    "            \"Highlights NVIDIA achieved progress since its previous earnings announcement \"\n",
    "            \"in these areas:  Data Center Second-quarter revenue was a record $10.32 billion, \"\n",
    "            \"up 141% from the previous quarter and up 171% from a year ago. Announced that the \"\n",
    "            \"NVIDIA® GH200 Grace™ Hopper™ Superchip for complex AI and HPC workloads is shipping \"\n",
    "            \"this quarter, with a second-generation version with HBM3e memory expected to ship \"\n",
    "            \"in Q2 of calendar 2024. \"},\n",
    "\n",
    "{\"query\": \"What is Bank of America's rating on Target?\",\n",
    " \"answer\": \"Buy\",\n",
    " \"context\": \"Here are some of the tickers on my radar for Thursday, Oct. 12, taken directly from \"\n",
    "            \"my reporter’s notebook: It’s the one-year anniversary of the S&P 500′s bear market bottom \"\n",
    "            \"of 3,577. Since then, as of Wednesday’s close of 4,376, the broad market index \"\n",
    "            \"soared more than 22%.  Hotter than expected September consumer price index, consumer \"\n",
    "            \"inflation. The Social Security Administration issues announced a 3.2% cost-of-living \"\n",
    "            \"adjustment for 2024.  Chipotle Mexican Grill (CMG) plans price increases. Pricing power. \"\n",
    "            \"Cites consumer price index showing sticky retail inflation for the fourth time \"\n",
    "            \"in two years. Bank of America upgrades Target (TGT) to buy from neutral. Cites \"\n",
    "            \"risk/reward from depressed levels. Traffic could improve. Gross margin upside. \"\n",
    "            \"Merchandising better. Freight and transportation better. Target to report quarter \"\n",
    "            \"next month. In retail, the CNBC Investing Club portfolio owns TJX Companies (TJX), \"\n",
    "            \"the off-price juggernaut behind T.J. Maxx, Marshalls and HomeGoods. Goldman Sachs \"\n",
    "            \"tactical buy trades on Club names Wells Fargo (WFC), which reports quarter Friday, \"\n",
    "            \"Humana (HUM) and Nvidia (NVDA). BofA initiates Snowflake (SNOW) with a buy rating.\"\n",
    "            \"If you like this story, sign up for Jim Cramer’s Top 10 Morning Thoughts on the \"\n",
    "            \"Market email newsletter for free. Barclays cuts price targets on consumer products: \"\n",
    "            \"UTZ Brands (UTZ) to $16 per share from $17. Kraft Heinz (KHC) to $36 per share from \"\n",
    "            \"$38. Cyclical drag. J.M. Smucker (SJM) to $129 from $160. Secular headwinds. \"\n",
    "            \"Coca-Cola (KO) to $59 from $70. Barclays cut PTs on housing-related stocks: Toll Brothers\"\n",
    "            \"(TOL) to $74 per share from $82. Keeps underweight. Lowers Trex (TREX) and Azek\"\n",
    "            \"(AZEK), too. Goldman Sachs (GS) announces sale of fintech platform and warns on \"\n",
    "            \"third quarter of 19-cent per share drag on earnings. The buyer: investors led by \"\n",
    "            \"private equity firm Sixth Street. Exiting a mistake. Rise in consumer engagement for \"\n",
    "            \"Spotify (SPOT), says Morgan Stanley. The analysts hike price target to $190 per share \"\n",
    "            \"from $185. Keeps overweight (buy) rating. JPMorgan loves elf Beauty (ELF). Keeps \"\n",
    "            \"overweight (buy) rating but lowers price target to $139 per share from $150. \"\n",
    "            \"Sees “still challenging” environment into third-quarter print. The Club owns shares \"\n",
    "            \"in high-end beauty company Estee Lauder (EL). Barclays upgrades First Solar (FSLR) \"\n",
    "            \"to overweight from equal weight (buy from hold) but lowers price target to $224 per \"\n",
    "            \"share from $230. Risk reward upgrade. Best visibility of utility scale names.\"},\n",
    "\n",
    "{\"query\": \"Who is NVIDIA's partner for the driver assistance system?\",\n",
    " \"answer\": \"MediaTek\",\n",
    " \"context\":   \"Automotive Second-quarter revenue was $253 million, down 15% from the previous \"\n",
    "              \"quarter and up 15% from a year ago. Announced that NVIDIA DRIVE Orin™ is powering \"\n",
    "              \"the new XPENG G6 Coupe SUV’s intelligent advanced driver assistance system. \"\n",
    "              \"Partnered with MediaTek, which will develop mainstream automotive systems on \"\n",
    "              \"chips for global OEMs, which integrate new NVIDIA GPU chiplet IP for AI and graphics.\"},\n",
    "\n",
    "{\"query\": \"What was the rate of decline in 3rd quarter sales?\",\n",
    " \"answer\": \"20% year-on-year.\",\n",
    " \"context\": \"Nokia said it would cut up to 14,000 jobs as part of a cost cutting plan following \"\n",
    "            \"third quarter earnings that plunged. The Finnish telecommunications giant said that \"\n",
    "            \"it will reduce its cost base and increase operation efficiency to “address the \"\n",
    "            \"challenging market environment. The substantial layoffs come after Nokia reported \"\n",
    "            \"third-quarter net sales declined 20% year-on-year to 4.98 billion euros. Profit over \"\n",
    "            \"the period plunged by 69% year-on-year to 133 million euros.\"},\n",
    "\n",
    "{\"query\": \"What was professional visualization revenue in the quarter?\",\n",
    " \"answer\": \"$379 million\",\n",
    " \"context\": \"Gaming Second-quarter revenue was $2.49 billion, up 11% from the previous quarter and up \"\n",
    "            \"22% from a year ago. Began shipping the GeForce RTX™ 4060 family of GPUs, \"\n",
    "            \"bringing to gamers NVIDIA Ada Lovelace architecture and DLSS, starting at $299.\"\n",
    "            \"Announced NVIDIA Avatar Cloud Engine, or ACE, for Games, a custom AI model \"\n",
    "            \"foundry service using AI-powered natural language interactions to transform games \"\n",
    "            \"by bringing intelligence to non-playable characters. Added 35 DLSS games, including \"\n",
    "            \"Diablo IV, Ratchet & Clank: Rift Apart, Baldur’s Gate 3 and F1 23, as well as Portal: \"\n",
    "            \"Prelude RTX, a path-traced game made by the community using NVIDIA’s RTX Remix creator tool.\"\n",
    "            \"Professional Visualization Second-quarter revenue was $379 million, up 28% from the \"\n",
    "            \"previous quarter and down 24% from a year ago.  Announced three new desktop \"\n",
    "            \"workstation RTX GPUs based on the Ada Lovelace architecture — NVIDIA RTX 5000, RTX 4500 \"\n",
    "            \"and RTX 4000 — to deliver the latest AI, graphics and real-time rendering, which are \"\n",
    "            \"shipping this quarter. Announced a major release of the NVIDIA Omniverse platform, \"\n",
    "            \"with new foundation applications and services for developers and industrial \"\n",
    "            \"enterprises to optimize and enhance their 3D pipelines with OpenUSD and \"\n",
    "            \"generative AI.  Joined with Pixar, Adobe, Apple and Autodesk to form the \"\n",
    "            \"Alliance for OpenUSD to promote the standardization, development, evolution and \"\n",
    "            \"growth of Universal Scene Description technology.\"},\n",
    "\n",
    "\n",
    "{\"query\": \"What is the executive's title?\",\n",
    " \"answer\": \"Senior Vice President, Event Planning ('SVP') of the Workforce Optimization Division.\",\n",
    " \"context\": \"2.1. Duties and Responsibilities and Extent of Service. During the Employment Period, \"\n",
    "            \"Executive shall serve as Senior Vice President, Event Planning (“SVP”) of the Employer’s \"\n",
    "            \"Workforce Optimization Division. In such role, Executive will report to the Board of \"\n",
    "            \"Directors of Employer (the “Board”) and shall devote substantially all of his business time \"\n",
    "            \"and attention and his best efforts and ability to the operations of Employer and its subsidiaries. \"\n",
    "            \"Executive shall be responsible for running Employer’s day-to-day operations and shall perform \"\n",
    "            \"faithfully, diligently and competently the duties and responsibilities of a SVP and such other \"\n",
    "            \"duties and responsibilities as directed by the Board and are consistent with such position. \"\n",
    "            \"The foregoing shall not be construed as preventing Executive from (a) making passive \"\n",
    "            \"investments in other businesses or enterprises consistent with Employer’s code of conduct, \"\n",
    "            \"or (b) engaging in any other business activity consistent with Employer’s code of conduct; \"\n",
    "            \"provided that Executive seeks and obtains the prior approval of the Board before engaging \"\n",
    "            \"in any other business activity. In addition, it shall not be a violation of this Agreement \"\n",
    "            \"for Executive to participate in civic or charitable activities, deliver lectures, fulfill \"\n",
    "            \"speaking engagements, teach at educational institutions, and/or manage personal investments \"\n",
    "            \"(subject to the immediately preceding sentence); provided that such activities do not \"\n",
    "            \"interfere in any substantial respect with the performance of Executive’s responsibilities \"\n",
    "            \"as an employee in accordance with this Agreement. Executive may also serve on one or more \"\n",
    "            \"corporate boards of another company (and committees thereof) upon giving advance notice \"\n",
    "            \"to the Board prior to commencing service on any other corporate board.\"},\n",
    "\n",
    "{\"query\": \"According to the CFO, what led to the increase in cloud revenue?\",\n",
    " \"answer\": \"Focused execution by our sales teams and partners\",\n",
    " \"context\": \"'The world's most advanced AI models \"\n",
    "            \"are coming together with the world's most universal user interface - natural language - \"\n",
    "            \"to create a new era of computing,' said Satya Nadella, chairman and chief \"\n",
    "            \"executive officer of Microsoft. 'Across the Microsoft Cloud, we are the platform \"\n",
    "            \"of choice to help customers get the most value out of their digital spend and innovate \"\n",
    "            \"for this next generation of AI.' 'Focused execution by our sales teams and partners \"\n",
    "            \"in this dynamic environment resulted in Microsoft Cloud revenue of $28.5 billion, \"\n",
    "            \"up 22% (up 25% in constant currency) year-over-year,' said Amy Hood, executive \"\n",
    "            \"vice president and chief financial officer of Microsoft.\\n\"},\n",
    "\n",
    "{\"query\": \"Which company is located in Nevada?\",\n",
    " \"answer\": \"North Industries\",\n",
    " \"context\": \"To send notices to Blue Moon Tech, mail to their headquarters at: \"\n",
    "            \"555 California Street, San Francisco, California 94123. To send notices to North Industries, mail to\"\n",
    "            \"their principal U.S. offices at: 19832 32nd Avenue, Las Vegas, Nevada 23593.\\nTo send notices \"\n",
    "            \"to Red River Industries, send to: One Red River Road, Stamford, Connecticut 08234.\"},\n",
    "\n",
    "{\"query\": \"When can termination after a material breach occur?\",\n",
    " \"answer\": \"If the breach is not cured within 15 days of notice of the breach.\",\n",
    " \"context\": \"This Agreement shall remain in effect until terminated. Either party may terminate this \"\n",
    "            \"agreement, any Statement of Work or Services Description for convenience by giving the other \"\n",
    "            \"party 30 days written notice. Either party may terminate this Agreement or any work order or \"\n",
    "            \"services description if the other party is in material breach or default of any obligation \"\n",
    "            \"that is not cured within 15 days’ notice of such breach. The TestCo agrees to pay all fees \"\n",
    "            \"for services performed and expenses incurred prior to the termination of this Agreement. \"\n",
    "            \"Termination of this Agreement will terminate all outstanding Statement of Work or Services \"\n",
    "            \"Description entered into under this agreement.\"},\n",
    "\n",
    "{\"query\": \"What is a headline summary in 10 words or less?\",\n",
    " \"answer\": \"Joe Biden is the 46th President of the United States.\",\n",
    " \"context\": \"Joe Biden's tenure as the 46th president of the United States began with \"\n",
    "            \"his inauguration on January 20, 2021. Biden, a Democrat from Delaware who \"\n",
    "            \"previously served as vice president under Barack Obama, \"\n",
    "            \"took office following his victory in the 2020 presidential election over \"\n",
    "            \"Republican incumbent president Donald Trump. Upon his inauguration, he \"\n",
    "            \"became the oldest president in American history.\"},\n",
    "\n",
    "{\"query\": \"Who are the two people that won elections in Georgia?\",\n",
    " \"answer\": \"Jon Ossoff and Raphael Warnock\",\n",
    " \"context\": \"Though Biden was generally acknowledged as the winner, \"\n",
    "            \"General Services Administration head Emily W. Murphy \"\n",
    "            \"initially refused to begin the transition to the president-elect, \"\n",
    "            \"thereby denying funds and office space to his team. \"\n",
    "            \"On November 23, after Michigan certified its results, Murphy \"\n",
    "            \"issued the letter of ascertainment, granting the Biden transition \"\n",
    "            \"team access to federal funds and resources for an orderly transition. \"\n",
    "            \"Two days after becoming the projected winner of the 2020 election, \"\n",
    "            \"Biden announced the formation of a task force to advise him on the \"\n",
    "            \"COVID-19 pandemic during the transition, co-chaired by former \"\n",
    "            \"Surgeon General Vivek Murthy, former FDA commissioner David A. Kessler, \"\n",
    "            \"and Yale University's Marcella Nunez-Smith. On January 5, 2021, \"\n",
    "            \"the Democratic Party won control of the United States Senate, \"\n",
    "            \"effective January 20, as a result of electoral victories in \"\n",
    "            \"Georgia by Jon Ossoff in a runoff election for a six-year term \"\n",
    "            \"and Raphael Warnock in a special runoff election for a two-year term. \"\n",
    "            \"President-elect Biden had supported and campaigned for both \"\n",
    "            \"candidates prior to the runoff elections on January 5.On January 6, \"\n",
    "            \"a mob of thousands of Trump supporters violently stormed the Capitol \"\n",
    "            \"in the hope of overturning Biden's election, forcing Congress to \"\n",
    "            \"evacuate during the counting of the Electoral College votes. More \"\n",
    "            \"than 26,000 National Guard members were deployed to the capital \"\n",
    "            \"for the inauguration, with thousands remaining into the spring.\"},\n",
    "\n",
    "{\"query\": \"What is the list of the top financial highlights for the quarter?\",\n",
    " \"answer\": \"•Revenue: $52.9 million, up 10% in constant currency;\\n\"\n",
    "           \"•Operating income: $22.4 billion, up 15% in constant currency;\\n\"\n",
    "           \"•Net income: $18.3 billion, up 14% in constant currency;\\n\"\n",
    "           \"•Diluted earnings per share: $2.45 billion, up 14% in constant currency.\",\n",
    "           \"context\": \"Microsoft Cloud Strength Drives Third Quarter Results \\nREDMOND, Wash. — April 25, 2023 — \"\n",
    "           \"Microsoft Corp. today announced the following results for the quarter ended March 31, 2023,\"\n",
    "           \" as compared to the corresponding period of last fiscal year:\\n· Revenue was $52.9 billion\"\n",
    "           \" and increased 7% (up 10% in constant currency)\\n· Operating income was $22.4 billion \"\n",
    "           \"and increased 10% (up 15% in constant currency)\\n· Net income was $18.3 billion and \"\n",
    "           \"increased 9% (up 14% in constant currency)\\n· Diluted earnings per share was $2.45 \"\n",
    "           \"and increased 10% (up 14% in constant currency).\\n\"},\n",
    "\n",
    "{\"query\": \"What is a list of the key points?\",\n",
    " \"answer\": \"•Stocks rallied on Friday with stronger-than-expected U.S jobs data and increase in \"\n",
    "           \"Treasury yields;\\n•Dow Jones gained 195.12 points;\\n•S&P 500 added 1.59%;\\n•Nasdaq Composite rose \"\n",
    "           \"1.35%;\\n•U.S. economy added 438,000 jobs in August, better than the 273,000 expected;\\n\"\n",
    "           \"•10-year Treasury rate trading near the highest level in 14 years at 4.58%.\",\n",
    "           \"context\": \"Stocks rallied Friday even after the release of stronger-than-expected U.S. jobs data \"\n",
    "           \"and a major increase in Treasury yields.  The Dow Jones Industrial Average gained 195.12 points, \"\n",
    "           \"or 0.76%, to close at 31,419.58. The S&P 500 added 1.59% at 4,008.50. The tech-heavy \"\n",
    "           \"Nasdaq Composite rose 1.35%, closing at 12,299.68. The U.S. economy added 438,000 jobs in \"\n",
    "           \"August, the Labor Department said. Economists polled by Dow Jones expected 273,000 \"\n",
    "           \"jobs. However, wages rose less than expected last month.  Stocks posted a stunning \"\n",
    "           \"turnaround on Friday, after initially falling on the stronger-than-expected jobs report. \"\n",
    "           \"At its session low, the Dow had fallen as much as 198 points; it surged by more than \"\n",
    "           \"500 points at the height of the rally. The Nasdaq and the S&P 500 slid by 0.8% during \"\n",
    "           \"their lowest points in the day.  Traders were unclear of the reason for the intraday \"\n",
    "           \"reversal. Some noted it could be the softer wage number in the jobs report that made \"\n",
    "           \"investors rethink their earlier bearish stance. Others noted the pullback in yields from \"\n",
    "           \"the day’s highs. Part of the rally may just be to do a market that had gotten extremely \"\n",
    "           \"oversold with the S&P 500 at one point this week down more than 9% from its high earlier \"\n",
    "           \"this year.  Yields initially surged after the report, with the 10-year Treasury rate trading \"\n",
    "           \"near its highest level in 14 years. The benchmark rate later eased from those levels, but \"\n",
    "           \"was still up around 6 basis points at 4.58%.  'We’re seeing a little bit of a give back \"\n",
    "           \"in yields from where we were around 4.8%. [With] them pulling back a bit, I think that’s \"\n",
    "           \"helping the stock market,' said Margaret Jones, chief investment officer at Vibrant Industries \"\n",
    "           \"Capital Advisors. 'We’ve had a lot of weakness in the market in recent weeks, and potentially \"\n",
    "           \"some oversold conditions.'\"}\n",
    "\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 388,
     "referenced_widgets": [
      "795a24acc52a4334a0f355cb33e7b841",
      "7f5115a036524531b1a144c06adebb97",
      "91e5e40e422f43a7ac092b0701f92cba",
      "b42bb6a1b8844ff6a08ff243dedeb2c7",
      "fa30ff08a49a4167baa76bf7cb594f50",
      "4c7cd0ca4814454ab349d7867a1d8cab",
      "fafb4c3ee8cd4781b2e6ebff9122fb11",
      "9d1f5ad555604599833a5dcbd39d38c7",
      "7d732fe7e8d14b7f911df38eb79ef50e",
      "ede38c29bd7341ef92aca8eefd83ff15",
      "c14a213cb14d4eba85ca4eec8a6f7961",
      "f155c615e275447a83870d0b3acfad05",
      "0908b8a5858f4e9baf97b71d83609b9b",
      "e8bf9841cbd840efbd620f42ef55bc7c",
      "31623eeb16da49bfbed0681627b3cae0",
      "ae1313e57ff44dad83068bd754a7d479",
      "2f4e36e1a6d945439acddb7026028d19",
      "78bcb4c6ea254f108909d8051523c17b",
      "6e6856b84a1e487b93bcdef5fce1a190",
      "21ce79e851cb4e7ea247f433d73204b5",
      "e742feb817f845e0a5709fb37540d541",
      "e59148c840e74bcca98f878aceef74dd",
      "7e65489c12f54b688117b4841497e009",
      "e6f4fa682d3246398d9f98858b020a75",
      "f3c31b94c820409dade607ad73b489c9",
      "ff7a14a5ac6e47998303328896d85122",
      "bafc77deb95049f7980a63ed26e83d64",
      "005025f07eeb4aacb37c6d505dfd7065",
      "6989643b74c0490cacc3708f666f2baf",
      "97f1cbada54c4d8ead283f21dbacd7f2",
      "c17e9115d13846b893204ce8c371e9f8",
      "8d573c80a48e4b44aee94f65fe8d6dbc",
      "50a73768b5c041f28ac4595ce850d97a",
      "7d030a854a944287879bc1a8b79879a8",
      "fce6e5ed3978484d9471b8aa9504fcb5",
      "bb5de60fa62d4d449bcfda8a3e8aecef",
      "30276c2e709e496d9e60a58dd6d73cb1",
      "50c68373e0f94520b86be47ef8337e65",
      "afbb8bf73f2e45959e2d65f08ce58441",
      "3cc039d8b3304741a98ee0a498cd07c8",
      "cc67aaf2edeb4a4d8b75e526ecf7079a",
      "210c96ec80c645cf9ab6857d6eda04ac",
      "e2c4add149414f9a990497a75a6a6aa3",
      "006d79a0ab524b2ebce0d5dcefa48dda",
      "9581442011bb49fea052252fd3769c2e",
      "e0df690926bb40278b368a3c018f529e",
      "0b63902f9884455e9a08705d8c7835b5",
      "6518cd1e5ee848a18a6bcd8388157151",
      "73ea88dd98d84e75a61c475d0f836b10",
      "25cc1e4cfe954c08ae0808b2c09e0805",
      "879f323ab7284aa7b8af1930289f9142",
      "d10fd2224e5f4c31a112d917b87f4cf2",
      "45911ab8466245628e5af793587159b7",
      "fedd18c336ed4ae5a0774a514c07cc6c",
      "fcfbcf368af34932a91d4f1f9f6f5304"
     ]
    },
    "id": "PnJ3mNCVGLY4",
    "outputId": "3a417be6-3343-43a4-e810-5399d4ac57e5"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " > Loading Model: bling-answer-tool...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: UserWarning: \n",
      "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
      "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
      "You will be able to reuse this secret in all of your notebooks.\n",
      "Please note that authentication is recommended but still optional to access public models or datasets.\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/huggingface_hub/file_download.py:1194: UserWarning: `local_dir_use_symlinks` parameter is deprecated and will be ignored. The process to download files to a local folder has been updated and do not rely on symlinks anymore. You only need to pass a destination folder as`local_dir`.\n",
      "For more details, check out https://huggingface.co/docs/huggingface_hub/main/en/guides/download#download-files-to-local-folder.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "795a24acc52a4334a0f355cb33e7b841",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Fetching 4 files:   0%|          | 0/4 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f155c615e275447a83870d0b3acfad05",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       ".gitattributes:   0%|          | 0.00/1.62k [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7e65489c12f54b688117b4841497e009",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "config.json:   0%|          | 0.00/247k [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7d030a854a944287879bc1a8b79879a8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "README.md:   0%|          | 0.00/1.50k [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9581442011bb49fea052252fd3769c2e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "bling-answer.gguf:   0%|          | 0.00/669M [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(f\"\\n > Loading Model: {model_name}...\")\n",
    "prompter = Prompt().load_model(model_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "1XLuwODRGYvk",
    "outputId": "16286067-5682-46cb-ff44-55ef94a9f435"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " > Model bling-answer-tool load time: 15.268526554107666\n"
     ]
    }
   ],
   "source": [
    "t1 = time.time()\n",
    "print(f\"\\n > Model {model_name} load time: {t1-t0 }\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "d6jTsiAdNrPo",
    "outputId": "20c25bda-92e1-4427-a381-41164fd08e44"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "1. Query: What is the total amount of the invoice?\n",
      "LLM Response: 22,500.00\n",
      "Gold Answer: $22,500.00\n",
      "LLM Usage: {'input': 209, 'output': 9, 'total': 218, 'metric': 'tokens', 'processing_time': 2.0669240951538086}\n",
      "\n",
      "2. Query: What was the amount of the trade surplus?\n",
      "LLM Response: 62.4 billion yen ($416.6 million)\n",
      "Gold Answer: 62.4 billion yen ($416.6 million)\n",
      "LLM Usage: {'input': 178, 'output': 15, 'total': 193, 'metric': 'tokens', 'processing_time': 1.638265609741211}\n",
      "\n",
      "3. Query: What was Microsoft's revenue in the 3rd quarter?\n",
      "LLM Response: 52.9 billion, up 7% (up 10% in constant currency)\n",
      "Gold Answer: $52.9 billion\n",
      "LLM Usage: {'input': 203, 'output': 20, 'total': 223, 'metric': 'tokens', 'processing_time': 2.359246015548706}\n",
      "\n",
      "4. Query: When did the LISP machine market collapse?\n",
      "LLM Response: 1987\n",
      "Gold Answer: 1987.\n",
      "LLM Usage: {'input': 435, 'output': 4, 'total': 439, 'metric': 'tokens', 'processing_time': 2.45987606048584}\n",
      "\n",
      "5. Query: When will employment start?\n",
      "LLM Response: April 16, 2012\n",
      "Gold Answer: April 16, 2012.\n",
      "LLM Usage: {'input': 186, 'output': 11, 'total': 197, 'metric': 'tokens', 'processing_time': 0.8680579662322998}\n",
      "\n",
      "6. Query: What is the current rate on 10-year treasuries?\n",
      "LLM Response: 6 basis points at 4.58%\n",
      "Gold Answer: 4.58%\n",
      "LLM Usage: {'input': 552, 'output': 10, 'total': 562, 'metric': 'tokens', 'processing_time': 2.0527071952819824}\n",
      "\n",
      "7. Query: What is the governing law?\n",
      "LLM Response: State of Massachusetts\n",
      "Gold Answer: State of Massachusetts\n",
      "LLM Usage: {'input': 338, 'output': 3, 'total': 341, 'metric': 'tokens', 'processing_time': 1.1315374374389648}\n",
      "\n",
      "8. Query: What is the amount of the base salary?\n",
      "LLM Response: 200,000\n",
      "Gold Answer: $200,000.\n",
      "LLM Usage: {'input': 200, 'output': 7, 'total': 207, 'metric': 'tokens', 'processing_time': 0.8254244327545166}\n",
      "\n",
      "9. Query: Is the expected gross margin greater than 70%?\n",
      "LLM Response: Yes, 71.5% > 70%.\n",
      "Gold Answer: Yes, between 71.5% and 72.%\n",
      "LLM Usage: {'input': 339, 'output': 13, 'total': 352, 'metric': 'tokens', 'processing_time': 1.3918354511260986}\n",
      "\n",
      "10. Query: What is Bank of America's rating on Target?\n",
      "LLM Response: TRADE: Buy\n",
      "Gold Answer: Buy\n",
      "LLM Usage: {'input': 787, 'output': 6, 'total': 793, 'metric': 'tokens', 'processing_time': 3.8873860836029053}\n",
      "\n",
      "11. Query: Who is NVIDIA's partner for the driver assistance system?\n",
      "LLM Response: MediaTek\n",
      "Gold Answer: MediaTek\n",
      "LLM Usage: {'input': 136, 'output': 3, 'total': 139, 'metric': 'tokens', 'processing_time': 0.5586395263671875}\n",
      "\n",
      "12. Query: What was the rate of decline in 3rd quarter sales?\n",
      "LLM Response: 20%\n",
      "Gold Answer: 20% year-on-year.\n",
      "LLM Usage: {'input': 149, 'output': 3, 'total': 152, 'metric': 'tokens', 'processing_time': 0.607762336730957}\n",
      "\n",
      "13. Query: What was professional visualization revenue in the quarter?\n",
      "LLM Response: Not Found.\n",
      "Gold Answer: $379 million\n",
      "LLM Usage: {'input': 423, 'output': 3, 'total': 426, 'metric': 'tokens', 'processing_time': 1.4556689262390137}\n",
      "\n",
      "14. Query: What is the executive's title?\n",
      "LLM Response: Senior Vice President, Event Planning\n",
      "Gold Answer: Senior Vice President, Event Planning ('SVP') of the Workforce Optimization Division.\n",
      "LLM Usage: {'input': 410, 'output': 9, 'total': 419, 'metric': 'tokens', 'processing_time': 1.498265027999878}\n",
      "\n",
      "15. Query: According to the CFO, what led to the increase in cloud revenue?\n",
      "LLM Response: 1.  Focused execution by the sales teams and partners in this dynamic environment.  2.  Microsoft Cloud revenue of $28.5 billion, up 22% (up 25% in constant currency).  3.  Amy Hood, executive vice president and chief financial officer of Microsoft.\n",
      "Gold Answer: Focused execution by our sales teams and partners\n",
      "LLM Usage: {'input': 176, 'output': 67, 'total': 243, 'metric': 'tokens', 'processing_time': 2.3003711700439453}\n",
      "\n",
      "16. Query: Which company is located in Nevada?\n",
      "LLM Response: North Industries\n",
      "Gold Answer: North Industries\n",
      "LLM Usage: {'input': 129, 'output': 4, 'total': 133, 'metric': 'tokens', 'processing_time': 0.5510938167572021}\n",
      "\n",
      "17. Query: When can termination after a material breach occur?\n",
      "LLM Response: 30 days written notice\n",
      "Gold Answer: If the breach is not cured within 15 days of notice of the breach.\n",
      "LLM Usage: {'input': 162, 'output': 5, 'total': 167, 'metric': 'tokens', 'processing_time': 0.6938717365264893}\n",
      "\n",
      "18. Query: What is a headline summary in 10 words or less?\n",
      "LLM Response: Joe Biden's tenure as the 46th president of the United States began with his inauguration on January 20, 2021.\n",
      "Gold Answer: Joe Biden is the 46th President of the United States.\n",
      "LLM Usage: {'input': 117, 'output': 36, 'total': 153, 'metric': 'tokens', 'processing_time': 1.4063897132873535}\n",
      "\n",
      "19. Query: Who are the two people that won elections in Georgia?\n",
      "LLM Response: Jon Ossoff and Raphael Warnock\n",
      "Gold Answer: Jon Ossoff and Raphael Warnock\n",
      "LLM Usage: {'input': 365, 'output': 12, 'total': 377, 'metric': 'tokens', 'processing_time': 1.9793884754180908}\n",
      "\n",
      "20. Query: What is the list of the top financial highlights for the quarter?\n",
      "LLM Response: •Revenue was $52.9 billion and increased 7% (up 10% in constant currency)\n",
      "•Operating income was $22.4 billion and increased 10% (up 15% in constant currency)\n",
      "•Net income was $18.3 billion and increased 9% (up 14% in constant currency)\n",
      "•Diluted earnings per share was $2.45 and increased 10% (up 14% in constant currency)\n",
      "Gold Answer: •Revenue: $52.9 million, up 10% in constant currency;\n",
      "•Operating income: $22.4 billion, up 15% in constant currency;\n",
      "•Net income: $18.3 billion, up 14% in constant currency;\n",
      "•Diluted earnings per share: $2.45 billion, up 14% in constant currency.\n",
      "LLM Usage: {'input': 203, 'output': 110, 'total': 313, 'metric': 'tokens', 'processing_time': 4.0941481590271}\n",
      "\n",
      "21. Query: What is a list of the key points?\n",
      "LLM Response: •Stocks rallied Friday even after the release of stronger-than-expected U.S. jobs data and a major increase in Treasury yields.\n",
      "•The Dow Jones Industrial Average gained 195.12 points, or 0.76%, to close at 31,419.58.\n",
      "•The S&P 500 added 1.59% at 4,008.50.\n",
      "•The tech-heavy Nasdaq Composite rose 1.35%, closing at 12,299.68.\n",
      "•The U.S. economy added 438,000 jobs in August, the Labor Department said. Economists polled by Dow Jones expected 273,000 jobs. However, wages rose less than expected last month.\n",
      "Gold Answer: •Stocks rallied on Friday with stronger-than-expected U.S jobs data and increase in Treasury yields;\n",
      "•Dow Jones gained 195.12 points;\n",
      "•S&P 500 added 1.59%;\n",
      "•Nasdaq Composite rose 1.35%;\n",
      "•U.S. economy added 438,000 jobs in August, better than the 273,000 expected;\n",
      "•10-year Treasury rate trading near the highest level in 14 years at 4.58%.\n",
      "LLM Usage: {'input': 546, 'output': 189, 'total': 735, 'metric': 'tokens', 'processing_time': 7.0252697467803955}\n",
      "\n",
      "Total processing time: 40.96032643318176 seconds\n"
     ]
    }
   ],
   "source": [
    "for i, entries in enumerate(test_list):\n",
    "  print(f\"\\n{i+1}. Query: {entries['query']}\")\n",
    "\n",
    "  output = prompter.prompt_main(entries[\"query\"],\n",
    "                                context=entries[\"context\"],\n",
    "                                prompt_name=\"default_with_context\",\n",
    "                                temperature=0.30)\n",
    "\n",
    "  llm_response = output[\"llm_response\"].strip(\"\\n\")\n",
    "  print(f\"LLM Response: {llm_response}\")\n",
    "\n",
    "  print(f\"Gold Answer: {entries['answer']}\")\n",
    "\n",
    "  print(f\"LLM Usage: {output['usage']}\")\n",
    "\n",
    "t2 = time.time()\n",
    "print(f\"\\nTotal processing time: {t2-t1} seconds\")"
   ]
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